Biology subjects

Zhang, N.

Publications and source records attributed to Zhang, N..

At least 181 records · Page 10Linked to original sources

bioRxiv2023

Induction of transmucosal protection by oral vaccination with an attenuated Chlamydia

Chlamydia muridarum has been used to study chlamydial pathogenesis since it induces mice to develop hydrosalpinx, a pathology observed in C. trachomatis-infected women. We identified a C. muridarum mutant that is no longer able to induce hydrosalpinx. In the current study, we evaluated the mutant as an attenuated vaccine. Following an intravaginal immunization with the mutant, mice were protected from hydrosalpinx induced by wild type C. muridarum. However, the mutant itself productively colonized the mouse genital tract and produced infectious organisms in vaginal swabs. Nevertheless, the mutant failed to produce infectious shedding in the rectal swabs following an oral inoculation. Importantly, mice orally inoculated with the mutant mounted transmucosal immunity against challenge infection of wild type C. muridarum in the genital tract. The protection was detected as early as day 3 following the challenge infection and the immunized mice were protected from any significant pathology in the upper genital tract. However, the same orally immunized mice failed to prevent the colonization of wild type C. muridarum in the gastrointestinal tract. The transmucosal immunity induced by the oral mutant was further validated in the airway. The orally vaccinated mice were protected from both lung infection and systemic toxicity caused by intranasally inoculated wild type C. muridarum although the same mice still permitted the gastrointestinal colonization by the wild type C. muridarum. These observations suggest that the mutant C. muridarum may be developed into an intracellular oral vaccine vector (or IntrOv) for selectively inducing transmucosal immunity in extra-gut tissues.

immunology↗

bioRxiv2023

Translational predictions of phase 2a first-in patient efficacy studies for antituberculosis drugs

BackgroundPhase 2a trials in tuberculosis typically use early bactericidal activity (EBA), the decline in sputum colony forming units (CFU) over 14 days, as the primary outcome for testing the efficacy of drugs as monotherapy. However, the cost of phase 2a trials can range from 7 to 19.6 million dollars on average, while more than 30% of drugs fail to progress to phase 3. Better utilizing preclinical data to predict and prioritize the most likely drugs to succeed will thus help accelerate drug development and reduce costs. We aim to predict clinical EBA using preclinical in vivo pharmacokinetic-pharmacodynamic (PKPD) data and a model-based translational pharmacology approach. Methods and FindingsFirst, mouse PK, PD and clinical PK models were compiled. Second, mouse PKPD models were built to derive an exposure response relationship. Third, translational prediction of clinical EBA studies was performed using mouse PKPD relationships and informed by clinical PK models and species-specific protein binding. Presence or absence of clinical efficacy was accurately predicted from the mouse model. Predicted daily decreases of CFU in the first 2 days of treatment and between day 2 and day 14 were consistent with clinical observations. ConclusionThis platform provides an innovative solution to inform or even replace phase 2a EBA trials, to bridge the gap between mouse efficacy studies and phase 2b and phase 3 trials, and to substantially accelerate drug development.

pharmacology and toxicology↗

bioRxiv2023

Integration of spatial and single-cell data across modalities with weak linkage

single-cell sequencing methods have enabled the profiling of multiple types of molecular readouts at cellular resolution, and recent developments in spatial barcoding, in situ hybridization, and in situ sequencing allow such molecular readouts to retain their spatial context. Since no technology can provide complete characterization across all layers of biological modalities within the same cell, there is pervasive need for computational cross-modal integration (also called diagonal integration) of single-cell and spatial omics data. For current methods, the feasibility of cross-modal integration relies on the existence of highly correlated, a priori "linked" features. When such linked features are few or uninformative, a scenario that we call "weak linkage", existing methods fail. We developed MaxFuse, a cross-modal data integration method that, through iterative co-embedding, data smoothing, and cell matching, leverages all information in each modality to obtain high-quality integration. MaxFuse is modality-agnostic and, through comprehensive benchmarks on single-cell and spatial ground-truth multiome datasets, demonstrates high robustness and accuracy in the weak linkage scenario. A prototypical example of weak linkage is the integration of spatial proteomic data with single-cell sequencing data. On two example analyses of this type, we demonstrate how MaxFuse enables the spatial consolidation of proteomic, transcriptomic and epigenomic information at single-cell resolution on the same tissue section.

bioinformatics↗

bioRxiv2023

Niche differential gene expression analysis in spatial transcriptomics data identifies context-dependent cell-cell interactions

Single cells influence, and are shaped by, their local spatial niche. Technologies for in situ measurement of gene expression at the transcriptome scale have enabled the detailed profiling of the spatial distributions of cell types in tissue as well as the interrogation of local signaling patterns between cell types [1]. Towards these goals, we propose a new statistical procedure called niche-differential expression (niche-DE) analysis. Niche-DE identifies cell-type specific niche-associated genes, defined as genes whose expression within a specific cell type is significantly up- or down-regulated, in the context of specific spatial niches. We develop effective and interpretable measures for global false discovery control and show, through the analysis of data sets generated by myriad protocols, that the method is robust to technical issues such as over-dispersion and spot swapping. Niche-DE can be applied to low-resolution spot- and ROI-based spatial transcriptomics data as well as data that is single-cell or subcellular in resolution. Based on niche-DE, we also develop a procedure to reveal the ligand-receptor signaling mechanisms that underlie niche-differential gene expression patterns. When applied to 10x Visium data from liver metastases of colorectal cancer, niche-DE identifies marker genes for cancer-associated fibroblasts and macrophages and elucidates ligand-receptor crosstalk patterns between tumor cells, macrophages and fibroblasts. Co-detection by indexing (CODEX) was performed on the same patient samples, to corroborate the niche-DE results.

bioinformatics↗

bioRxiv2022

FOXC2 marks and maintains the primitive spermatogonial stem cells subpopulation in the adult testis

In adult mammals, spermatogenesis embodies the complex developmental process from spermatogonial stem cells (SSCs) to spermatozoa. At the top of this developmental hierarchy lie a series of SSC subpopulations. Their individual identities as well as the relationships with each other, however, remain largely elusive. Using single-cell analysis and lineage tracing, we discovered both in mice and humans the quiescent adult SSC subpopulation marked specifically by forkhead box protein C2 (FOXC2). All spermatogenic progenies can be derived from FOXC2+ SSCs and the ablation of FOXC2+ SSCs led to the depletion of the undifferentiated spermatogonia pool. During germline regeneration, FOXC2+ SSCs were activated and able to completely restore the process. Germ cell specific Foxc2 knockout resulted in an accelerated exhaustion of SSCs and eventually led to male infertility. Furthermore, FOXC2 prompts the expressions of negative regulators of cell cycle thereby ensures the SSCs reside in quiescence. Thus, this work proposes that the quiescent FOXC2+ SSCs are essential for maintaining the homeostasis and regeneration of spermatogenesis in adult mammals.

developmental biology↗

bioRxiv2022

Moderate High Temperature is Beneficial or Detrimental Depending on Carbon Availability in the Green Alga Chlamydomonas reinhardtii

High temperatures impair plant and algal growth and reduce food and biofuel production, but the underlying mechanisms remain elusive. The unicellular green alga Chlamydomonas reinhardtii is a superior model to study heat responses in photosynthetic cells due to its fast growth rate, many similarities in cellular processes to land plants, simple and sequenced genome, and ample genetic and genomics resources. Chlamydomonas grows in light by photosynthesis and/or with the externally supplied organic carbon source, acetate. Most of the published research about Chlamydomonas heat responses used acetate-containing medium. Understanding how organic carbon sources affect heat responses is important for the algal industry but understudied. We cultivated Chlamydomonas wild-type cultures under highly controlled conditions in photobioreactors at control of 25{degrees}C, moderate high temperature of 35{degrees}C, or acute high temperature of 40{degrees}C with and without constant acetate supply for 1- or 4-days. Our results showed that 35{degrees}C increased algal growth with constant acetate supply but reduced algal growth without sufficient acetate. The overlooked and dynamic effects of 35{degrees}C could be explained by induced carbon metabolism, including acetate uptake and assimilation, glyoxylate cycle, gluconeogenesis pathways, and glycolysis. Acute high temperature at 40{degrees}C for more than 2 days was lethal to algal cultures with and without constant acetate supply. Our research provides insights to understand algal heat responses and help improve thermotolerance in photosynthetic cells. HighlightWe revealed the overlooked, dynamic effects of moderate high temperature in algae depending on carbon availability and demonstrated the importance of carbon metabolism in thermotolerance of photosynthetic cells.

plant biology↗

bioRxiv2022

MERISTEM-DEFECTIVE/DEFECTIVELY ORGANIZED TRIBUTARIES2 regulates the balance between stemness and differentiation in the root meristem through RNA splicing control.

Plants respond to environmental stresses through controlled stem cell maintenance and meristem activity. One level of transcriptional control is RNA alternative splicing. However the mechanistic link between stress, meristem function and RNA splicing is poorly understood. The MERISTEM-DEFECTIVE (MDF)/DEFECTIVELY ORGANIZED TRIBUTARIES (DOT2) gene of Arabidopsis encodes a SR-related family protein, required for meristem function and leaf vascularization, and is the likely orthologue of the human SART1 and yeast snu66 splicing factors. MDF is required for the correct splicing and expression of key transcripts associated with root meristem function. We identified RSZ33 and ACC1, both known to regulate cell patterning, as splicing targets required for MDF function in the meristem. MDF expression is modulated by osmotic and cold stress, associated with differential splicing and specific isoform accumulation and shuttling between nucleus and cytosol, and acts in part via a splicing target SR34. We propose a model in which MDF controls splicing in the root meristem to promote stemness and repress stress response and cell differentiation pathways. Summary statementThe protein MERISTEM-DEFECTIVE regulates Arabidopsis meristem function through its role as a splicing factor, mediated through splicing targets RSZ33, ACC1 and SR34.

plant biology↗

bioRxiv2022

Robust identification of extrachromosomal DNA and genetic variants using multiple genetic abnormality sequencing (MGA-Seq)

Genomic abnormalities, including structural variation (SV), copy number variation (CNV), single-nucleotide polymorphism (SNP), homogenously staining regions (HSR) and extrachromosomal DNA (ecDNA), are strongly associated with cancer, rare diseases and infertility. A robust technology to simultaneously detect these genomic abnormalities is highly desired for clinical diagnosis and basic research. In this study, we developed a simple and cost-effective method - multiple genetic abnormality sequencing (MGA-Seq) - to simultaneously detect SNPs, CNVs, SVs, ecDNA and HSRs in a single tube. This method has been successfully applied in both cancer cell lines and clinical tumour samples and revealed that focal amplification in tumour tissue is substantially heterogeneous. Notably, we delineated the architecture of focal amplification and the ecDNA network by MGA-Seq, which facilitated the exploration of the regulation of gene expression in ecDNA. This method could be extensively applied for diagnosis and may greatly facilitate the investigation of the genomic mechanism for genetic diseases.

genomics↗

bioRxiv2022

Development of a novel oral treatment that rescues gait ataxia and retinal degeneration in a phenotypic mouse model of familial dysautonomia.

Familial Dysautonomia (FD) is a rare neurodegenerative disease caused by a splicing mutation in the Elongator complex protein 1 gene (ELP1). This mutation leads to the skipping of exon 20 and a tissue-specific reduction of ELP1 protein, mainly in the central and peripheral nervous systems. FD is a complex neurological disorder accompanied by severe gait ataxia and retinal degeneration. There is currently no effective treatment to restore ELP1 protein expression in individuals with FD, and the disease is ultimately fatal. After identifying kinetin as a small molecule able to correct the ELP1 splicing defect, we worked on its optimization to generate novel splicing modulator compounds (SMCs) that can be used in patients. Here, we optimize the potency, efficacy, and bio-distribution of second-generation kinetin derivatives to develop an oral treatment for FD that can efficiently pass the blood-brain barrier and correct the ELP1 splicing defect in the nervous system. We demonstrate that the novel compound, PTC258, efficiently restores correct ELP1 splicing in mouse tissues, including brain, and most importantly, prevents the progressive neuronal degeneration that is characteristic of FD. Postnatal oral administration of PTC258 to the phenotypic mouse model TgFD9;Elp1{Delta}20/flox increases full-length ELP1 transcript in a dose-dependent manner and leads to a two-fold increase in functional ELP1 protein in the brain. Remarkably, PTC258 treatment improves survival, gait ataxia, and retinal degeneration in the phenotypic FD mice. Our findings highlight the great therapeutic potential of this novel class of small molecules as an oral treatment for FD.

genetics↗

bioRxiv2022

Quartet metabolite reference materials for assessing inter-laboratory reliability and data integration of metabolomic profiling

Various laboratory-developed metabolomic methods lead to big challenges in inter-laboratory comparability and effective integration of diverse datasets. As part of the Quartet Project, we established a publicly available suite of four metabolite reference materials derived from B-lymphoblastoid cell lines from a family quartet of parents and monozygotic twin daughters. We generated comprehensive LC-MS based metabolomic data from the Quartet reference materials using targeted and untargeted strategies in different laboratories. High variabilities in the qualitative and quantitative metabolomic measurements were observed across laboratories. Moreover, the Quartet multi-sample-based quality metrics were developed for objectively assessing the reliability of metabolomic profiling in detecting intrinsic biological differences among difference groups of samples. Importantly, the ratio-based metabolomic profiling, by scaling the absolute values of a study sample relative to those of a universal reference sample, enables data integration in long-term measurements across difference laboratories or platforms. Thus, we constructed the ratio-based high-confidence reference datasets between two reference samples, providing "ground truth" for inter-laboratory proficiency test, which enables objective assessment of various metabolomic methods. Our study provided the community with rich resources and best practice for objective assessment of inter-laboratory measurements and data integration, ensuring reliable large-scale and longitudinal metabolomic profiling.

systems biology↗

bioRxiv2022

Ratio-based quantitative multiomics profiling using universal reference materials empowers data integration

Multiomics profiling is a powerful tool to characterize the same samples with complementary features orchestrating the genome, epigenome, transcriptome, proteome, and metabolome. However, the lack of ground truth hampers the objective assessment of and subsequent choice from a plethora of measurement and computational methods aiming to integrate diverse and often enigmatically incomparable omics datasets. Here we establish and characterize the first suites of publicly available multiomics reference materials of matched DNA, RNA, proteins, and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters, providing built-in truth defined by family relationship and the central dogma. We demonstrate that the "ratio"-based omics profiling data, i.e., by scaling the absolute feature values of a study sample relative to those of a concurrently measured universal reference sample, were inherently much more reproducible and comparable across batches, labs, platforms, and omics types, thus empower the horizontal (within-omics) and vertical (cross-omics) data integration in multiomics studies. Our study identifies "absolute" feature quantitation as the root cause of irreproducibility in multiomics measurement and data integration, and urges a paradigm shift from "absolute" to "ratio"-based multiomics profiling with universal reference materials.

systems biology↗

bioRxiv2022

Correcting batch effects in large-scale multiomic studies using a reference-material-based ratio method

Batch effects are notorious technical variations that are common in multiomic data and may result in misleading outcomes. With the era of big data, tackling batch effects in multiomic integration is urgently needed. As part of the Quartet Project for quality control and data integration of multiomic profiling, we comprehensively assess the performances of seven batch-effect correction algorithms (BECAs) for mitigating the negative impact of batch effects in multiomic datasets, including transcriptomics, proteomics, and metabolomics. Performances are evaluated based on accuracy of identifying differentially expressed features, robustness of predictive models, and the ability of accurately clustering cross-batch samples into their biological sample groups. Ratio-based method is more effective and widely applicable than others, especially in cases when batch effects are highly confounded with biological factors of interests. We further provide practical guidelines for the implementation of ratio-based method using universal reference materials profiled with study samples. Our findings show the promise for eliminating batch effects and enhancing data integration in increasingly large-scale, cross-batch multiomic studies.

systems biology↗

bioRxiv2022

Not just with the natives, but phylogenetic relationship between stages of the invasion process determines invasion success of alien plant species

Darwin proposed two alternate hypotheses on the invasion success of alien plant species based on their close or distant phylogenetic relationship with the natives. Here we tested these hypotheses along the invasion process at large spatio-temporal scale. Using two abundance-based phylogenetic metrics for the native and alien flora of China, our study showed that invasion success of alien plant species is influenced by the phylogenetic relationship with native and alien species of different invasion stages. Phylogenetic similarity with the native species helps the alien ones to introduce and naturalize, but phylogenetic dissimilarity with the natives facilitates invasion success. The co-occurrence of invasive and naturalized aliens also formed more clustered assemblages, showed specialized responses to environmental stress, and provided temporal stability to the phylogenetic measures. The native-alien phylogenetic relationship is dynamic across spatial, environmental, and taxonomic scales. Therefore, assessing Darwins naturalization conundrum at different gradients of community assembly process is important.

ecology↗

bioRxiv2022

Bacillus velezensis SQR9 sways the rhizosphere community and its sociality toward cooperation and plant growth promotion

According to the Lotka-Volterra competition model, intraspecific competition in plant-associated microbial communities should be stronger than interspecific competition. However, there is limited information on whether microbial communities follow this pattern and how disturbance by a newcomer affects them. Given the increasing popularity of probiotics, filling this knowledge gap could help guide future coexistence research. Here, we show that inoculation with a known probiotic, B. velezensis SQR9 shifts species co-occurrence patterns by decreasing the diversity of more distant species and promoting the growth of more closely related species, especially within the Bacillus community. By testing the sociality of Bacillus rhizosphere isolates, we then demonstrated that SQR9 increases the frequency of cooperative interactions in the Bacillus community, which may contribute to the promotion of plant growth. Finally, we provide an ecosystem framework comprising the strains genetic relatedness, metabolic niche space and social compatibility for the efficient and reliable assembly of Bacillus consortia. These findings shed new light on the ecological mechanisms underlying the beneficial effects of probiotics on host fitness.

microbiology↗

bioRxiv2022

Curation of the Deep Green list of unannotated green lineage proteins to enable structural and functional characterization

An explosion of sequenced genomes and predicted proteomes enabled by low cost deep sequencing has revolutionized biology. Unfortunately, protein functional annotation is more complex, and has not kept pace with the sequencing revolution. We identified unannotated proteins in three model organisms representing distinct parts of the green lineage (Viridiplantae); Arabidopsis thaliana (dicot), Setaria viridis (monocot), and Chlamydomonas reinhardtii (Chlorophyte alga). Using similarity searching we found the subset of unannotated proteins that were conserved between these species and defined them as Deep Green proteins. Informatic, genomic, and structural predictions were leveraged to begin inferring functional information about Deep Green genes and proteins. The Deep Green set was enriched for proteins with predicted chloroplast targeting signals that are predictive of photosynthetic or plastid functions. Strikingly, structural predictions using AlphaFold and comparisons to known structures show that a significant proportion of Deep Green proteins may possess novel protein tertiary structures. The Deep Green genes and proteins provide a starting resource of high value targets for further investigation of potentially new protein structures and functions that are conserved in the green lineage.

plant biology↗

bioRxiv2022

The Quartet Data Portal: integration of community-wide resources for multiomics quality control

The implementation of quality control for multiomic data requires the widespread use of well-characterized reference materials, reference datasets, and related resources. The Quartet Data Portal was built to facilitate community access to such rich resources established in the Quartet Project. A convenient platform is provided for users to request the DNA, RNA, protein, and metabolite reference materials, as well as multi-level datasets generated across omics, platforms, labs, protocols, and batches. Interactive visualization tools are offered to assist users to gain a quick understanding of the reference datasets. Crucially, the Quartet Data Portal continuously collects, evaluates, and integrates the community-generated data of the distributed Quartet multiomic reference materials. In addition, the portal provides analysis pipelines to assess the quality of user-submitted multiomic data. Furthermore, the reference datasets, performance metrics, and analysis pipelines will be improved through periodic review and integration of multiomic data submitted by the community. Effective integration of the evolving technologies via active interactions with the community will help ensure the reliability of multiomics-based biological discoveries. The Quartet Data Portal is accessible at https://chinese-quartet.org. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

systems biology↗

bioRxiv2022

Quartet DNA reference materials and datasets for comprehensively evaluating germline variants calling performance

Current methods for evaluating the accuracy of germline variant calls are restricted to easy-to-detect high-confidence regions, thus ignoring a substantial portion of difficult variants beyond the benchmark regions. We established four DNA reference materials from immortalized cell lines derived from a Chinese Quartet including parents and monozygotic twins. We integrated benchmark calls of 4.2 million small variants and 15,000 structural variants from multiple platforms and bioinformatic pipelines for evaluating the reliability of germline variant calls inside the benchmark regions. The genetic built-in-truth of the Quartet family design not only improved sensitivity of benchmark calls by removing additional false positive variants with apparently high quality, but also enabled estimation of the precision of variants calls outside the benchmark regions. Batch effects of variant calling in large-scale DNA sequencing efforts can be effectively identified with the concurrent use of the Quartet DNA reference materials along with study samples, and can be alleviated by training a machine learning model with the Quartet reference datasets to remove potential artifact calls. Matched RNA and protein reference materials were also established in the Quartet project, thereby enabling benchmark calls constructed from DNA reference materials for evaluation of variants calling performance on RNA and protein data. The Quartet DNA reference materials from this study are a resource for objective and comprehensive assessment of the accuracy of germline variant calls throughout the whole-genome regions.

bioinformatics↗

bioRxiv2022

Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling

As an indispensable tool for transcriptome-wide analysis of differential gene expression, RNA sequencing (RNAseq) has demonstrated great potential in clinical applications. However, the lack of multi-group RNA reference materials of biological relevance and the corresponding reference datasets for assessing the reliability of RNAseq hampers its wide clinical applications wherein the underlying biological differences among study groups are often small. As part of the Quartet Project for quality control and data integration of multiomic profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets using multi-batch RNAseq datasets, providing "ground truth" for benchmarking. Moreover, Quartet-sample-based quality metrics were developed for assessing reliability of RNAseq technology in terms of intra-batch proficiency and cross-batch reproducibility. The small intrinsic biological differences among the Quartet samples enable sensitive assessment of performance of transcriptomic measurements. The Quartet RNA reference materials combined with the reference datasets can be served as unique resources for assessing data quality and improving reliability of transcriptomic profiling.

genetics↗